The vast amount of information that has, and continues to be, accumulated on the molecular interactions that constitute bioregulatory networks demands a clear and concise method of diagrammatic representation. We urgently need the equivalent of electronic circuit diagrams as an aid to comprehension and analysis. Unlike standard circuit diagrams or classical metabolic pathway diagrams, bioregulatory networks are dominated by controls based on mult-protein complexes and protein modification patterns, where enzymes frequently are substrates of other enzymes. These, and other unique features of bioregulatory networks, make representation by classical methods intractable. To address this problem, a novel convention for molecular interaction maps was proposed and applied to the network controlling cell proliferation, DNA repair, and apoptosis (Kohn 1999 Molec. Biol. Cell 10: 2703-34; Kohn 2001 Chaos 11: 84-97). This method has received considerable attention as a potential standard. During the past year, this project focused on the preparation of new and updated molecular interaction maps to be incorporated into the integrated bioinformatics facility being developed in our Laboratory by John N. Weinstein and his staff. We focus our attention on those regulatory networks that are likely targets for new cancer therapies, therapies that would be tailored to take advantage of vulnerabilities caused by specific genomic defects in the cells of particular tumors. The maps show all of the known interactions and modifications of the protein species of interest and give an overview of potential pathways and feedback loops. Any of this information can be accessed easily by way of indices and map coordinates. Cogent information that may be useful for therapy design is included in annotation lists linked to interaction labels on the maps. Literature references are included, in order to help determine where updating is required. We find that molecular interaction maps are very helpful for understanding complex networks, as well as for the design and interpretation of functional experiments. Also during the past year, the molecular interaction map procedure was applied successfully to DNA microarray data generated in a study of gene expression changes associated with the development of multi-drug resistance in a human prostate cancer cell line. The experiments were conducted in our Laboratory by the group led by John N. Weinstein, who found that the cells resisted apoptosis responses to several types of drugs and radiation. The microarray data showed altered expression of a disproportionately high number of genes related to apoptosis. However the direction of the altered expression often appeared to be in the direction opposite to what would have been expected for resistance to apoptosis. A molecular interaction map of the pathways involving the altered genes led to an explanation and to a general model. The model proposes that downstream pathway alterations that impair apoptosis occur first, and that these alterations relax constraints on changes in upstream survival pathways that would otherwise lead to apoptosis. This study has been submitted for publication.